Introduction :

Joining an existing data engineering squad as staff augmentation, you bring graph data modeling and analytics skills on top of a PySpark/SQL data engineering foundation, working within the squad's existing lead and stand-ups.

As an embedded Data Engineer, you bring graph analytics to life on top of a PySpark/Snowflake data foundation.

Note: Shares a common PySpark/Snowflake base with "Data Engineer - Power BI Modelling" - source together, differentiate on graphing vs. semantic-modeling depth at interview.

Key responsibilities :

- Model graph data: Design and implement graph data models and analytics (e.g., Neo4j or similar).

- Build pipelines: Develop PySpark/Python and SQL pipelines feeding the Snowflake environment.

- Integrate with reporting: Support Power BI consumption of graph and pipeline outputs where needed.

- Collaborate: Operate inside the existing squad structure with no separate delivery lead required.

- Ensure quality: Validate data accuracy and performance of graph queries and pipelines.

- Explore GenAI: Apply GenAI techniques to relevant use cases as opportunities arise.

Must-have qualifications :

- Python and PySpark

- SQL

- Graph data modeling / graph databases

Preferred :

- Power BI (optional, depending on seniority)

- Snowflake; Dataiku